Hajime Uno

13.3k citations
189 papers · 8.5k indexed · 4 hit papers · h-index 44

Impact in

Papers in

    • Statistical Methods in Clinical Trials 24
    • Statistical Methods and Inference 18
    • Advanced Causal Inference Techniques 16
    • Cancer survivorship and care 17

Hajime Uno

174 papers receiving 8.4k citations

Hit Papers

Tumor aneuploidy correlates with markers of immune evasion and with reduced response to immunotherapy 2017 · 848 citations
8482011202620162021250500750

Peers

Hajime Uno
Comparison fields: 5 of 171
  • Statistics and Probability 998
  • Virology 367
  • Nephrology 549
  • Oncology 2.0k
  • Cancer Research 1.0k
Replace Theodore Karrison with:
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Alan D. Hutson United States
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Hajime Uno relative to Theodore Karrison United States Theodore Karrison's profile →
Citations per field
00.5×3.6×
Theodore Karrison · 1×
Citations per year

Countries citing papers authored by Hajime Uno

Since Specialization
Citations

This map shows the geographic impact of Hajime Uno's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Hajime Uno with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hajime Uno more than expected).

Fields of papers citing papers by Hajime Uno

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hajime Uno. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Hajime Uno. The network helps show where Hajime Uno may publish in the future.

Co-authors

The 25 scholars most cited alongside Hajime Uno, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Hajime Uno Line = papers co-authored together Hajime Uno links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 20250
3 20250
4 20243
5 20240
6 202313
7 20230
8 20231
9 202058
10 202029
11 201938
12
Tumor aneuploidy correlates with markers of immune evasion and with reduced response to immunotherapy
Hit paper breakdown →
2017848
13 201713
14 201652
15 2015170
16 2014120
17 201039
18 2010182
19
Solitary pulmonary granuloma caused by Mycobacterium avium-intracellulare complex.
200710
20
Study on estimating information-processing demand for driver using subsidiary task methodology
20051

About Hajime Uno

Hajime Uno is a scholar working on Statistics and Probability, Oncology, Cancer Research, Hematology and Virology, having authored 189 papers that have together received 8.5k indexed citations. Recurring topics across this work include Health Systems, Economic Evaluations, Quality of Life (26 papers), Statistical Methods in Clinical Trials (24 papers), Palliative Care and End-of-Life Issues (24 papers), Childhood Cancer Survivors' Quality of Life (20 papers), Cancer Genomics and Diagnostics (20 papers), Statistical Methods and Inference (18 papers), Cancer survivorship and care (17 papers) and Advanced Causal Inference Techniques (16 papers). The work is most often cited by research in Statistics and Probability (998 citations), Virology (367 citations), Nephrology (549 citations), Oncology (2.0k citations) and Cancer Research (1.0k citations). Hajime Uno has collaborated with scholars based in United States, Japan and Canada. Frequent co-authors include L. J. Wei, Tianxi Cai, Lü Tian, Scott D. Solomon, Teresa Davoli, Eric C. Wooten, Stephen J. Elledge, Ralph B. D’Agostino, Michael Pencina and Marc A. Pfeffer. Their work appears in journals such as Journal of Clinical Oncology, Statistics in Medicine, JAMA Network Open, Blood and JAMA Oncology.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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